Senior QA Engineer (Automation, Data Quality)

Introduction

DigiEx Group is a global technology partner specializing in Innovation Software Development, AI-powered solutions, Tech Talent services, and Digital Transformation. Headquartered in Vietnam, DigiEx helps startups and enterprises worldwide build scalable digital products and high-performing engineering teams.

At DigiEx, we embrace an AI-first engineering culture, empowering every team member to leverage AI technologies to build smarter software, improve productivity, and continuously innovate.

Key Responsibilities

• Own the data quality and test automation strategy across ETL pipelines, data warehouses, and downstream reporting within client engagements.
• Design, develop, and maintain automated and manual validation suites covering data transformations, integrity, completeness, and reconciliation.
• Define and enforce data quality standards and SLAs, establishing validation rules and quality thresholds before pipelines go live.
• Lead QA gates for data and reporting releases, ensuring data meets quality standards before reaching production dashboards or operational workflows.
• Validate data mappings and transformations across source systems, ETL processes, and target data platforms.
• Lead root-cause analysis and defect resolution for data discrepancies, ensuring issues are clearly documented and tracked through remediation.
• Build and maintain automated regression coverage for reporting workflows, dashboards, campaign reporting, and operational data feeds.
• Drive improvements to QA automation frameworks, testing standards, and data governance practices across the engagement.

Requirements

Must Have

• Bachelor's degree or higher in Computer Science, Information Technology, Information Systems, or a related field.
• 5+ years of experience in Data QA, Data Testing, or Data Engineering, with strong hands-on experience in data pipeline testing and automation.
• Strong SQL skills for complex data validation, reconciliation, and integrity checks across large-scale datasets.
• Hands-on experience with ETL testing and validating data transformations in Snowflake, Redshift, BigQuery, or equivalent platforms.
• Strong experience with data test automation, using dbt Tests, Great Expectations, pytest, or equivalent frameworks.
• Experience designing and implementing QA strategies, regression coverage, and automated quality gates for data platforms.
• Strong analytical and root-cause analysis skills, with the ability to distinguish data quality issues from business logic or source-system issues.
• Experience with Jira or equivalent defect management tools, including clear documentation, impact assessment, and remediation tracking.
• Ability to review AI-generated data pipeline code and transformation logic, identifying correctness, integrity, security, and quality issues.
• Good understanding of data governance, PII handling, and compliance in regulated environments.
• Business-level English, with the ability to communicate testing results, defects, and release readiness with technical and client stakeholders.

Nice to Have

• Experience in healthcare, pharmaceutical, or life sciences data environments.
• Experience integrating automated data testing into CI/CD pipelines, using dbt Cloud, Airflow, or equivalent tools.
• Familiarity with Tableau, Power BI, or other BI platforms and validating dashboard metrics against source data.
• Knowledge of HIPAA, SOC 2, or similar compliance requirements.